JDS Journal of Data Science 1683-86021680-743X1680-743X School of Statistics, Renmin University of China JDS1208D 10.6339/25-JDS1208D Education in Data Science Discussion of “Addressing the Challenges of AI-Generated Assignment Submissions in Education: Insights and Strategies”✩ ColumbusAlyssaacolumb1@jhu.edu1 Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA 21205

Main article: https://doi.org/10.6339/25-JDS1208.

Email: acolumb1@jhu.edu. 20261122026241264266 2026 The Author(s). Published by the School of Statistics and the Center for Applied Statistics, Renmin University of China.2026 Open access article under the CC BY license. academic assessment academic integrity AI-resilient assessment data science education generative AI in education References Darling-Hammond L, Flook L, Cook-Harvey C, Barron B, Osher D (2019). Implications for educational practice of the science of learning and development. Applied Developmental Science, 24(2): 97–140. https://doi.org/10.1080/10888691.2018.1537791 Michelene T, Wylie R (2014). The ICAP framework: Linking cognitive engagement to active learning outcomes. Educational Psychologist, 49(4): 219–243. https://doi.org/10.1080/00461520.2014.965823 Russo D (2024). Navigating the complexity of generative AI adoption in software engineering. ACM Transactions on Software Engineering and Methodology, 33(5): 1–50. https://doi.org/10.1145/3652154 Wang S, Xu L, Liu J, Zhai Y (2025). Addressing the challenges of AI-generated assignment submissions in education: Insights and strategies. Journal of Data Science, 24(1): 1–7. https://doi.org/10.6339/25-JDS1208 Weber-Wulff D, Anohina-Naumeca A, Bjelobaba S, Foltýnek T, Guerrero-Dib J, Popoola O, et al. (2023). Testing of detection tools for AI-generated text. International Journal for Educational Integrity, 19(26). https://doi.org/10.1007/s40979-023-00146-z